it recruiter · 1 hour ago
GenAI architect
United States
Full-time
Remote
Senior LevelIt Recruiter is seeking a GenAI Architect to design and lead the technical foundation for enterprise AI initiatives. The role involves defining enterprise AI reference architectures, designing end-to-end AI solutions, and ensuring governance and operational excellence in AI implementations.
Computer Games
Hiring Manager
Deepak Ghosh
Responsibilities
Define enterprise Al reference architectures that enable rapid experimentation, scalable deployment, and long-term maintainability
Design end-to-end Al solutions spanning data ingestion, model development, deployment, and monitoring layers
Ensure architectural decisions balance innovation with enterprise standards for security, performance, and cost optimization
Create reusable patterns, templates, and accelerators that reduce time-to-value for Al implementations
Architect data ecosystems that provide high-quality, accessible, and governed data for AI/ML workloads
Design MLOps pipelines enabling continuous integration, delivery, and monitoring of Al models at scale
Establish feature stores, model registries, and versioning frameworks that ensure reproducibility and traceability
Optimize data architectures for real-time inference, batch processing, and hybrid deployment scenarios
Define cloud-native Al platform strategies leveraging Azure, AWS, GCP, or hybrid environments
Evaluate and recommend Al/ML platforms, tools, and frameworks aligned with client capabilities and objectives
Design infrastructure architectures that optimize compute, storage, and networking for Al workloads
Ensure platform choices support scalability, cost efficiency, and future technology evolution
Embed governance, security, and compliance requirements into Al architecture from design phase
Design model explainability, bias detection, and fairness monitoring capabilities into solution architectures
Architect audit trails, lineage tracking, and access controls that meet regulatory requirements
Ensure architectures support responsible Al principles including transparency, accountability, and privacy
Translate business requirements into technical architectures that stakeholders across business and IT can understand
Guide cross-functional teams including data engineers, data scientists, and DevOps through implementation
Influence enterprise architecture decisions to ensure Al readiness across technology landscape
Serve as technical authority on Al initiatives, resolving design conflicts and ensuring architectural integrity
Qualification
Required
Design and lead the technical foundation for enterprise AI initiatives
Define enterprise AI reference architectures that enable rapid experimentation, scalable deployment, and long-term maintainability
Design end-to-end AI solutions spanning data ingestion, model development, deployment, and monitoring layers
Ensure architectural decisions balance innovation with enterprise standards for security, performance, and cost optimization
Create reusable patterns, templates, and accelerators that reduce time-to-value for AI implementations
Architect data ecosystems that provide high-quality, accessible, and governed data for AI/ML workloads
Design MLOps pipelines enabling continuous integration, delivery, and monitoring of AI models at scale
Establish feature stores, model registries, and versioning frameworks that ensure reproducibility and traceability
Optimize data architectures for real-time inference, batch processing, and hybrid deployment scenarios
Define cloud-native AI platform strategies leveraging Azure, AWS, GCP, or hybrid environments
Evaluate and recommend AI/ML platforms, tools, and frameworks aligned with client capabilities and objectives
Design infrastructure architectures that optimize compute, storage, and networking for AI workloads
Ensure platform choices support scalability, cost efficiency, and future technology evolution
Embed governance, security, and compliance requirements into AI architecture from design phase
Design model explainability, bias detection, and fairness monitoring capabilities into solution architectures
Architect audit trails, lineage tracking, and access controls that meet regulatory requirements
Ensure architectures support responsible AI principles including transparency, accountability, and privacy
Translate business requirements into technical architectures that stakeholders across business and IT can understand
Guide cross-functional teams including data engineers, data scientists, and DevOps through implementation
Influence enterprise architecture decisions to ensure AI readiness across technology landscape
Serve as technical authority on AI initiatives, resolving design conflicts and ensuring architectural integrity
Company
it recruiter
Hello! I'm a Middle it recruiter, Senior HR. I have ability to find & generate hr- ideas and implement them.
Founded in 2017г.Новосибирск, НСО, RU
51-200 employeesFunding
Current Stage
Growth StageCompany data provided by crunchbase